The effort to recruit and collect multidisciplinary data on a large number of subjects is of[unreadable] most benefit when attempting to use this information to provide practical guidelines for[unreadable] clinicians treating patients. In order to accomplish this, we will need to test the possible[unreadable] interactions among separate measures such as brain function, stress reactivity and underlying[unreadable] genetic structure. The purpose of this core will be to use a combination of model building[unreadable] techniques, similar to those used in models of medical risk, and a comprehensive collection of[unreadable] relevant biological and clinical measurements to begin the process of developing reliable[unreadable] models of treatment response for depressed patients. We will use state-of-the-art variable[unreadable] selection techniques to build and validate a clinical model for overall and treatment-specific[unreadable] response, and evaluate its predictive ability through the use of statistical techniques. In[unreadable] addition, we will be incorporating genetic information, which will require specialized estimation[unreadable] techniques in order to model the relationship with treatment response. Thus we will have a[unreadable] statistical geneticist (Michael Epstein, PhD) working closely with the core to provide expertise[unreadable] and supervision for any treatment response related analyses, and a specific member of the[unreadable] core designated for handling those techniques.